Lung cancer is the leading cause of cancer-related death in the world. Approximately, 1.2 million people are diagnosed with lung cancer all over the world per year. Despite the great progresses in cancer research over the last decades, lung cancer has a very low 5-year survival rate of 16% as compared to 89% for breast cancer, 65% for colon cancer, and 100% for prostate cancer (1). While lung cancer comprises only about 15% of new cancer diagnoses, it causes over 30% of all cancer-related deaths. Lung cancer is divided into 2 major clinicopathological classes: small cell lung cancer (SCLC, about 15% of all lung cancer) and non-small cell lung cancer (NSCLC, about 85%). The latter includes three major histological subtypes: squamous cell carcinoma (SCC, 40% of NSCLC), adenocarcinoma (AD, 40% of NSCLC) and large cell carcinoma (10% of NSCLC) (2). NSCLC is commonly treated with surgery, while SCLC usually responds better to chemotherapy and radiotherapy. For NSCLC, curative surgery is efficacious only in those who are diagnosed sufficiently early. Unfortunately, more than 70% of the patients are diagnosed only at an advanced stage, which results in a lost opportunity for curative surgical resection, and poor prognosis. To improve the survival of patients with lung cancer, identifying reliable biomarkers for early diagnosis, prognosis prediction, and monitoring treatment response remain urgently needed.
Proteomic analysis, a powerful tool for global evaluation of protein expression, has been widely applied in cancer research. Quantitative protein expression profiling allows efficient identification of accurate and reproducible differential expression values for proteins in multiple biological samples. Comparison of protein expression profiles between tumors and normal tissues and among different tumors may lead to discovery of clinically useful tumor biomarkers, new therapeutic targets and elucidation of molecular mechanisms of cancers (3, 4). Several previous studies have focused on the application of comparative proteomics in screening differentially expressed proteins in cell line or clinical specimens of lung cancer (5-17). Approximately 300 proteins have been identified through these studies, including oncoproteins, signal transduction proteins, metabolic enzymes, and so on. However, few of them have been analyzed for their correlation with clinicopathological characteristics of lung cancer patients to investigate the value for clinical applications and their function in lung tumorigenesis. So far, none of these molecules identified is implemented in routine clinical use yet, and reliable biomarkers of lung cancer are urgently needed (18).